This invention relates generally to analyzing power plant event schedules, more particularly, to generating a financial report indicative of turbine maintenance event schedules by a business entity for a client.
Power plants utilizing gas turbines and steam turbines have become increasingly more complex thereby utilizing an increased quantity of various components. The power plant is periodically shut down to allow scheduled turbine maintenance events, facilitating maintenance and repair of the installed components, and to replace components which have reached the end of their useful life.
At least one known method utilizes a complex algorithm to determine the current operating condition of the power plant and the current hours on each part within the power plant. Utilizing a complex algorithm can be time consuming and costly since the algorithm generally relies on user information that is manually calculated to generate a schedule of parts replacement. If the manual calculations are incorrect, a part at or near the end of its life cycle may not be replaced during the shutdown resulting in an unanticipated plant shutdown in the future. Additionally, at least one known method utilizes a condition-based prediction of outages. The condition-based prediction requires an operator to inspect each part and manually enter the data into the algorithm. Manually entering data into the algorithm is time consuming and increases a likelihood that the algorithm with generate erroneous results.